|Abstract:||Optical tweezers utilize momentum transfer from confined electromagnetic fields within micro- and nanoscale objects to form non-invasive probes that serve to provide piconewton forces and detect motion with angstrom-level precision. This technique was discovered in the 1980s and has been found useful in a variety of research fields. However, optical tweezers, based on the use of high-numerical aperture objective lenses, suffer the diffraction limit, which hampers investigation on objects of interest on smaller scale. With sub-diffraction field confinement and enhancement properties, metallic nanostructures offer an alternative approach to bypass the diffraction limit, making a promising candidate for tools that help research on nanoscale systems. The intensity gradients produced within the nanometer-sized gaps of plasmonic bowtie nanoantennas (BNAs) are orders of magnitude larger than those of conventional optical tweezers. Accordingly, plasmon-enhanced gradient forces can both significantly relax constraints for microparticle manipulation and offer a route for improved nanoparticle trapping.
This thesis explores the near-field enhancement and confinement properties of arrays of pillar-supported Au bowtie nanoantennas (pBNAs), a new type of bowtie nanoantenna that evolves from its previous substrate-bound version, for plasmonic optical trapping and plasmonic film application. Compared to its precursors, the pBNAs exhibit larger field enhancement and thus steeper intensity gradient, which facilitates the particle trapping to a greater extent. In addition, by extending the metallic nanoantennas into a three-dimensional geometry, the heating effect originating from the strong intrinsic absorption property of the metallic structure leads to a tremendous increment in temperature. This thermal effect can be utilized to locally modify the morphological shape of pBNAs, resulting in interesting optical response from the arrays of pBNAs. This optical response allows the pBNAs to provide a film platform for recording information like audio signals, in either the time or frequency domain, with the capability of performing signal processing on chip.